Improving brain age prediction models: incorporation of amyloid status in Alzheimer's disease
Brain age prediction is a machine learning method that estimates an individual's
chronological age from their neuroimaging scans. Brain age indicates whether an …
chronological age from their neuroimaging scans. Brain age indicates whether an …
Multimodal biological brain age prediction using magnetic resonance imaging and angiography with the identification of predictive regions
Biological brain age predicted using machine learning models based on high‐resolution
imaging data has been suggested as a potential biomarker for neurological and …
imaging data has been suggested as a potential biomarker for neurological and …
Brain age estimation from MRI using a two-stage cascade network with ranking loss
As age increases, human brains will be aged, and people tend to experience cognitive
decline with a higher risk of neuro-degenerative disease and dementia. Recently, it was …
decline with a higher risk of neuro-degenerative disease and dementia. Recently, it was …
Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning
The brain's biological age has been considered as a promising candidate for a
neurologically significant biomarker. However, recent results based on longitudinal …
neurologically significant biomarker. However, recent results based on longitudinal …
Multimodal brain age prediction fusing morphometric and imaging data and association with cardiovascular risk factors
Introduction The difference between the chronological and biological brain age, called the
brain age gap (BAG), has been identified as a promising biomarker to detect deviation from …
brain age gap (BAG), has been identified as a promising biomarker to detect deviation from …
[HTML][HTML] Predicting brain age with complex networks: From adolescence to adulthood
In recent years, several studies have demonstrated that machine learning and deep learning
systems can be very useful to accurately predict brain age. In this work, we propose a novel …
systems can be very useful to accurately predict brain age. In this work, we propose a novel …
Multimodal brain age prediction with feature selection and comparison
Brain age, an estimated biological age from anatomical and/or functional brain imaging
data, and its deviation from the chronological age (brain age gap) have shown the potential …
data, and its deviation from the chronological age (brain age gap) have shown the potential …
Federation of brain age estimation in structural neuroimaging data
Brain age estimation is a widely used approach to evaluate the impact of various
neurological or psychiatric brain disorders on the brain developmental or aging process …
neurological or psychiatric brain disorders on the brain developmental or aging process …
Prediction of brain age using quantitative parameters of synthetic magnetic resonance imaging
S Bao, C Liao, N Xu, A Deng, Y Luo… - Frontiers in Aging …, 2022 - frontiersin.org
Objective Brain tissue changes dynamically during aging. The purpose of this study was to
use synthetic magnetic resonance imaging (syMRI) to evaluate the changes in relaxation …
use synthetic magnetic resonance imaging (syMRI) to evaluate the changes in relaxation …
Deep transfer learning of structural magnetic resonance imaging fused with blood parameters improves brain age prediction
Abstract Machine learning has been applied to neuroimaging data for estimating brain age
and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters …
and capturing early cognitive impairment in neurodegenerative diseases. Blood parameters …